With the advent of affordable, large-volume media-storage, many people and organizations are moving to massive digital archiving of images and documents. This movement ranges from simple home photograph collections to extremely sophisticated databases used by international corporations that include digital images and documents that may combine text with pictures or graphics. Unfortunately, searching and retrieving images and documents from these databases is not a trivial task.
Digitizing and scanning documents to create electronic versions, storing the electronic version in some form of electronic storage media, and subsequently searching these documents is not a new technology. In fact, there are numerous systems, commercial and otherwise, that have been developed over the past few years to deal with this very issue. One of the greatest advantages of such a searchable document system is the ability to quickly and efficiently search through large amounts of data for a very small percentage of “target” material.
Current document management systems perform reasonably well when working with documents that are mostly composed of textual information. The main methods of searching an image database are text-based, employing indexing, filenames, subject tags and so forth. Many techniques have been developed for analyzing images and extracting the textual information from those images and converting the text into a form, which can then be processed by the computer. This technology is generally known as Optical Character Recognition (OCR). OCR can be used to capture text from a document to form an index for a searchable database. The text can also be exported into other applications if desired. Relatively speaking, OCR is still in its infancy and no package can claim to be 100% accurate. Thus OCR used for indexing purposes, although very useful, still requires some manual verification, particularly if it is used to key primary fields.
OCR technology has made a significant step in automating the document imaging and searching process for documents composed mainly of text. However, OCR and computer automated processes in general are extremely limited when dealing with non-textual data, especially when contrasted with human abilities. The human visual perception system is excellent at high-speed analysis of images and the identification of objects within them. Indeed, humans can obtain information from an image far faster than from a textual representation of the same data.